Genetic algorithm diagnosis of individual cell frequencies in a coupled cavity chain

Genetic algorithms (GAs) are used to diagnose individual cell frequencies in a coupled cavity chain without any perturbing objects. The cell frequencies and couplings between the cells are determined in terms of the measured pass-band performance. The analysis simplifies the tuning processes and enables the tuning of the sealed cavities possible. The problem is solved as an optimization problem with GAs used as a function optimizer. The convergence is improved using the nonlinear least-squares method as a modification of the GAs, which also improves the precision of the solution. The effectiveness of the new technique is demonstrated through some numerical examples and the results are compared with those of the conventional GAs.